There are applications in which a depth measurement is needed for each point or pixel in a 2-dimensional (2D) image of a scene, which provides information about the distance between an object in the scene and the image capturing system. There is existing technology that provides such depth information in the form of a 3D point cloud that represents the 3D coordinates of real world surfaces within a given space. For instance, in computer stereo vision, 3D information is extracted from 2D digital images obtained by a solid state digital camera, by comparing captured information about the scene from two vantage points, and by examining the relative positions of objects in the images taken from the two vantage points. Another technique is referred to as structured light in which a known pattern of pixels is projected onto the scene. The way these patterns deform when striking the real world surfaces allows a vision system to calculate the depth and surface information of the objects in the scene. Invisible or imperceptible structured light is a technique that uses infrared light. Yet another technique is a time of flight camera that computes the distance or depth value based on the known speed of light and based on measuring the time of flight of a light signal between the camera and the reflecting object, for each point of the resulting image. In a time of flight camera, the entire scene is captured with each laser or light pulse. This is in contrast to a scanning light detection and ranging (LIDAR) system in which a pulsed light sweeps across the scene. It has been found, however, that such techniques may suffer from one or more of the following: excessive power consumption, limited x-y resolution, limited depth resolution or accuracy, limited frame rate, and long product development cycles.